wehub-resource-sync
109 lines
3.1 KiB
C++
109 lines
3.1 KiB
C++
// Copyright 2021 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include <cmath>
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#include <gmock/gmock.h>
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#include <gtest/gtest.h>
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#include "tensorflow/lite/kernels/custom_ops_register.h"
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#include "tensorflow/lite/kernels/test_util.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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#include "tensorflow/lite/testing/util.h"
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namespace tflite {
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namespace {
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template <typename T>
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tflite::TensorType GetTTEnum();
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template <>
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tflite::TensorType GetTTEnum<float>() {
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return tflite::TensorType_FLOAT32;
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}
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template <>
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tflite::TensorType GetTTEnum<double>() {
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return tflite::TensorType_FLOAT64;
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}
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class Atan2Model : public tflite::SingleOpModel {
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public:
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Atan2Model(tflite::TensorData y, tflite::TensorData x,
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tflite::TensorData output) {
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y_ = AddInput(y);
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x_ = AddInput(x);
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output_ = AddOutput(output);
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SetCustomOp("atan2", {}, ops::custom::Register_ATAN2);
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BuildInterpreter({GetShape(y_), GetShape(x_)});
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}
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int y_;
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int x_;
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int output_;
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template <typename T>
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std::vector<T> GetOutput(const std::vector<T>& y, const std::vector<T>& x) {
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PopulateTensor<T>(y_, y);
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PopulateTensor<T>(x_, x);
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Invoke();
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return ExtractVector<T>(output_);
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}
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};
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template <typename Float>
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class Atan2CustomTest : public ::testing::Test {
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public:
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using FloatType = Float;
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};
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using TestTypes = ::testing::Types<float, double>;
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TYPED_TEST_SUITE(Atan2CustomTest, TestTypes);
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TYPED_TEST(Atan2CustomTest, TestScalar) {
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using Float = typename TestFixture::FloatType;
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tflite::TensorData y = {GetTTEnum<Float>(), {}};
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tflite::TensorData x = {GetTTEnum<Float>(), {}};
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tflite::TensorData output = {GetTTEnum<Float>(), {}};
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Atan2Model m(y, x, output);
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auto got = m.GetOutput<Float>({0.0}, {0.0});
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ASSERT_EQ(got.size(), 1);
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EXPECT_FLOAT_EQ(got[0], 0.0);
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ASSERT_FLOAT_EQ(m.GetOutput<Float>({1.0}, {0.0})[0], M_PI / 2);
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ASSERT_FLOAT_EQ(m.GetOutput<Float>({0.0}, {1.0})[0], 0.0);
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ASSERT_FLOAT_EQ(m.GetOutput<Float>({-1.0}, {0.0})[0], -M_PI / 2);
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}
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TYPED_TEST(Atan2CustomTest, TestBatch) {
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using Float = typename TestFixture::FloatType;
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tflite::TensorData y = {GetTTEnum<Float>(), {4, 2, 1}};
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tflite::TensorData x = {GetTTEnum<Float>(), {4, 2, 1}};
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tflite::TensorData output = {GetTTEnum<Float>(), {4, 2, 1}};
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Atan2Model m(y, x, output);
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std::vector<Float> y_data = {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8};
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std::vector<Float> x_data = {0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1};
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auto got = m.GetOutput<Float>(y_data, x_data);
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ASSERT_EQ(got.size(), 8);
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for (int i = 0; i < 8; ++i) {
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EXPECT_FLOAT_EQ(got[i], std::atan2(y_data[i], x_data[i]));
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}
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}
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} // namespace
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} // namespace tflite
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